Detecting Temporal Pain Status of Postoperative Children from Facial Expression

Wu, Wenhao; Bi, Lei; Ren, Weihong; Nie, Wei; Lin, Ruihan; Liu, Zuode; Li, Sufang; Lin, Xi; Liu, Honghai

doi:10.1007/978-3-031-13841-6_63

Cited by 3 publications

(1 citation statement)

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“…In the study of Xu et al, they used a 0-10 numerical rating scale (self-report measure of pain) which is considered less accurate than the FLACC scale in children. Similarly, Wu et al (2022) reported a higher accuracy rate in detecting children pain from their facial expressions using an AI software analysis system than in assessing the pain by human volunteers [42]. These results suggest that AI-based pain assessment systems have the potential to accurately and reliably detect pain in pediatric patients.…”

Section: Discussionmentioning

confidence: 92%

Exploring the Role of Artificial Intelligence in Gauging Pain Severity caused by Local Dental Anesthetic Injections in Children: a cross-sectional study

Alkhouli,

Al-Nerabieah,

Al-Issa

et al. 2024

Preprint

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Pain assessment in children is essential for effective management, particularly during dental procedures. This study aimed to validate an AI software that utilizes facial expression analysis for pain assessment in children undergoing dental injections. A total of 300 children aged 6–9 years were included in the study. Pain assessment was conducted using both the AI software and the widely used FLACC scale. The AI software used a CNN algorithm to detected the action units (AUs) associated with pain. Statistical analysis, including correlation and regression, was performed to evaluate the performance of the AI software and the agreement between the FLACC scores and AI scores. The results showed a high sensitivity and specificity of the AI software in pain assessment, with an almost perfect agreement observed between the AI scores and the FLACC scores (r = 0.921). The AI model accurately detected pain levels in children, with comparable results for boys and girls. The findings of this study support the validity and reliability of the AI software for pain assessment in children undergoing dental injections. The AI software demonstrated high sensitivity and specificity in detecting pain.

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Section: Discussionmentioning

confidence: 92%